
Overview
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!
This Clinical Data Science course offered by Coursera in partnership with University of Colorado System provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data.
By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data.
This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment.
Applied Learning Project
Each course in the specialization culminates in a final project that is a practical application of the tools and technique you learned throughout the course. In these projects you will apply your skills to a real clinical data set using the free, fully hosted online data science environment provided by our industry partner, Google Cloud.
Skills You Will Gain:
- Data Quality Assessment
- Computational Phenotyping
- Implementation Science
- R Programming
- Clinical Text Mining
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Visit programme websiteProgramme Structure
Courses include:
- Introduction to Clinical Data Science
- Clinical Data Models and Data Quality Assessments
- Identifying Patient Populations
- Clinical Natural Language Processing
- Predictive Modeling and Transforming Clinical Practice
- Advanced Clinical Data Science
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- Flexible
Start dates & application deadlines
Language
Delivered
Disciplines
Data Science & Big Data View 578 other Short Courses in Data Science & Big Data in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate level
- Some programming experience and an interest in Clinical Data Science are required.
Make sure you meet all requirements
Visit programme websiteTuition Fee
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International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.